code: def _run(self, data, axes=None):  # type: ignore
      if axes is not None:
          if hasattr(axes, "__iter__") and len(axes.shape) > 0:
              try:
                  sq = np.expand_dims(data, axis=tuple(axes))
              except TypeError:
                  # numpy 1.18 supports axes as a tuple
                  if len(axes) == 1:
                      sq = np.expand_dims(data, axis=tuple(axes)[0])
                  else:
                      sq = data
                      for a in reversed(axes):
                          sq = np.expand_dims(sq, axis=a)
          else:
              sq = np.expand_dims(data, axis=axes)
      else:
          raise RuntimeError(
              "axes cannot be None for operator Unsqueeze (Unsqueeze_13)."
          )
      return (sq,)
  
file_path: onnx/onnx/reference/ops/op_unsqueeze.py
imports: import numpy
  from onnx.reference.op_run import OpRun
label_desc: Use image node_id 1 for calling the Unsqueeze_13 obj's underlying member method code with example usage: obj._run(data, axes) and returns: sq